Search

This study introduces the Orbit Weighting Scheme (OWS), a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval (IR) models, which have traditionally relied on weighting schemes like tf-idf and BM25. These conventional methods often struggle with accurately capturing document relevance, leading to inefficiencies in both retrieval performance and index size management. OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space, emphasizing term relationships and distribution patterns overlooked by existing models. Our research focuses on evaluating OWS's impact on model accuracy using Information Retrieval metrics like Recall, Precision, Interpolated Average Precision (IAP), and Mean Average Precision (MAP). Additionally, we assess OWS's effectiveness in reducing the inverted index size, crucial for model efficiency. We compare OWS-based retrieval models against others using different schemes, including tf-idf variations and BM25Delta. Results reveal OWS's superiority, achieving a 54% Recall and 81% MAP, and a notable 38% reduction in the inverted index size. This highlights OWS's potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS's capabilities in information retrieval methodologies. [ABSTRACT FROM AUTHOR]

The transformation of the food chain due to technological advances has had significant implications in regard to food safety. A noteworthy trend in this evolution relates to the emergence of new or previously unseen pathogens within products, thereby altering the landscape of foodborne illness epidemiology. The escalating frequency of these events underscores the need for a comprehensive re-evaluation of preventive strategies. The occurrence of novel species of bacteria, viruses, parasites, and unusual biotoxins from unexpected sources has challenged the previous limits that had been set to prevent foodborne illness outbreaks. The repercussions, ranging from detrimental effects on public health to economic burden, are influenced by a myriad of factors affecting the evolution of foodborne pathogens and emerging ailments. Among these factors are shifts in population demographics and behaviors, especially dietary patterns, as well as climate extremes, advances in more precise pathogen detection, microbial adaptation, evolving agricultural practices, and transformative changes within the food industry. This review critically examines the impact of technological metamorphosis along the food chain, encompassing production, processing, handling, packaging, storage, transportation, and industry demographics on the dynamics influencing the emergence of foodborne pathogens. Additionally, potential solutions to mitigate and manage this escalating issue are proposed. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the role of human resources management (HRM) in the development of total quality management (TQM) in Jordan's public and private sectors. This study used a quantitative research technique to assess the study sample's characteristics and investigate the link between HRM pract ices and TQM in Jordan's public and private sectors. There were 235 Jordanians in the research sample who were used by the public and private sectors in the HRM department. . A simple random sampling method was applied to ensure that every participant had a similar chance of being included in the research. A questionnaire with elements relating to HRM practices and total quality management was used to collect data. The results indicate that human resources planning, training, and performance evaluation play significant roles in the development of TQM in both the public and private sectors in Jordan. However, organizational bonuses demonstrate a weak relationship with TQM. As a result, institutional policymakers may greatly benefit from HRM and TQM by achieving strategic objectives and enhancing overall performance. This entails creating standards for quality, identifying risks, streamlining processes and guaranteeing customer satisfaction. The study recommendations can be made based on the mutual relationship between HRM and TQM to improve integration and make the most of this relationship such as by developing integrated training programs and integrating individual goals with quality goals. [ABSTRACT FROM AUTHOR]

After the Three Mile Island Unit 2 accident, regulatory bodies were concerned about the safety measures in design and operation corresponding to the operator's decisions and procedures for handling such off-normal transients. Several recommendations were proposed to analyze transients and accidents, improve and revise emergency operating procedures (EOPs), and conduct functional training. In this work, procedural paths were systematically studied to identify the problems in the diagnosis associated with a pilot-operated relief valve (PORV)-break loss-of-coolant accident (LOCA) as well as to suggest new indications for improving the EOPs. Operational parameters during PORV-break LOCA and pipeline-break small-break LOCA were analyzed using a generic pressurized water reactor simulator to compare and justify the symptoms between these two events. It was found that suggesting further indications mainly in the reactor cooling system and containment symptoms may improve the diagnosis of a PORV-break LOCA from the pipeline-break small-break LOCA. This paper presents a practical approach to evaluating diagnostic procedures to better understand operator recovery actions corresponding to reactor system response in dealing with a PORV-break LOCA. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) play an important role in the future of 5G and 6G communication networks. UAV-assisted communication offers the benefits of improved network capacity and coverage. A typical communication setup is for UAVs to connect users to the core network via a backhaul channel. Some of the challenges in such a setup include user-UAV association and management of the backhaul channel. These two challenges are greatly impacted by the positioning of the UAVs in the network. In this article, we address these challenges by considering a joint UAV placement and user association problem under data rate, signal to interference and noise ratio, and bandwidth constraints. To overcome this problem, a hybrid PSO-K-means clustering algorithm is used in two stages. In the first stage, we use a K-means algorithm to cluster users and determine their horizontal locations. In the second stage, we use particle swarm optimization (PSO) to find the efficient 3D position of UAVs to maximize various network designs, namely, the network-centric approach and the user-centric approach. The performance of the proposed solution is verified using simulation results. [ABSTRACT FROM AUTHOR]

Judicial decisions in the law and Sharia are implemented by following two methods, either voluntarily by the free will of the convicted person, or driven by fear of compulsory execution, and it is the second method carried out by the judiciary, by forcing the convicted person to implement the required consequent commitments and cries. The problem of this study lies In the adequacy of the legal texts and Islamic Sharia in finding solutions to implement judicial rulings and decisions, researchers will follow the descriptive and analytical approach, and the comparative approach whenever possible, and the researchers have reached set of results and recommendations, the most important of which was: The forced execution shall be upon legal litigation instated Through the enforcement departments of the judicial authority after exhausting the optional implementation method. As for the most important recommendations, it should be taken into account in the Islamic jurisprudence that the insolvent debtor is considered a debtor who is unable to fulfill his obligations, and not merely the claim of the person convicted of insolvency [ABSTRACT FROM AUTHOR]

The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new model to improve the efficiency and accuracy. This research presents a new model in synonyms extraction called Noun Based Distinctive Verbs (NBDV). During the documents' numerical representation phase, the NBDV replaces the traditional tf-idf weighting scheme with a novel weighting scheme called the Orbit Weighing Scheme (OWS). The OWS links the nouns to their semantic space by examining the singular verbs in each context. The weight of the term is determined by considering the three parameters: Verb_Noun Frequency, Verb_Noun Distribution, and Verb_Noun Distance. The Verb_Noun Distribution parameter is mathematically formulated to depict the semantic relation between the noun and a certain set of verbs that only appear in the context of this noun. We compared the new models with important models in the field, such as the Skip-Gram, the Continuous Bag of Words, and the GloVe model. The NBDV model was tested on both Arabic and English languages, and the results showed 47% recall and 51% precision in the dictionary-based evaluation and 57.5% precision in the human experts' evaluation. Comparing with the synonyms extraction based on tf.idf, the NBDV obtained 11% higher recall and 10% higher precision. Regarding the efficiency, we found that on average, the synonyms extraction of a single noun requires the process of 186 verbs, and in 63% of the runs; the number of singular verbs was less than 200. It is concluded that the developed method is efficient and processes the single run in linear time. [ABSTRACT FROM AUTHOR]

Sensor deployment positions play an important factor in determining target location estimation error performance in sensor networks employing received signal strength indicator measurements. The problem we investigate is as follows: Given a deployment area that has possibly non-uniform estimation error requirements and some initial sensor positions, then how can these sensors be deployed such that requirements are met as best as possible? We propose three variants of a low-complexity distributed strategy that require little information exchange between neighboring sensors. Each sensor locally calculates both the direction and magnitude of movement necessary to reduce the difference between achieved and required estimation errors at points within it sensing radius. The direction of movement is calculated as a weighted combination of these points. The weights can incorporate the error difference, number of sensors covering a point, the distance to a sensor and sensor density. Depending on the parameters chosen, three different weighing methods (namely, the density weighted centroid, error weighted centroid (EWC) and modified EWC) are proposed in this paper. We also provide an analytic derivation of the necessary distance a sensor should move. The proposed strategy is compared against a the RELOCATE algorithm and centralized generic genetic algorithm (GA) relocation method. Simulation results demonstrate that using the distributed strategy can achieve a comparable performance (within 10%) of the GA's performance and significantly outperform that of the RELOCATE. Sensor movement for different k. [ABSTRACT FROM AUTHOR]

The overall localization error performance for a sensor network employing quantized received signal strength (RSS) measurements largely depends on the number of bits used and their distribution. In this paper, we consider a rate-constrained bit allocation problem in which multiple points of interest (PoIs) are assigned possibly non-uniform error requirements. The main objective is to allocate a number of bits in order to satisfy error requirements as best as possible in a squared error sense. Due to the computational complexity of optimally solving the allocation problem, two novel low complexity allocation algorithms are proposed. The main idea behind these algorithms is to relate localization errors to corresponding bit density requirements. In the first algorithm, bit allocation is formulated as a sequential constrained convex optimization problem which can be solved with efficiency using available convex solvers. The second algorithm is a greedy version of the first algorithm in which sensors are selected for allocation based on the bit density differences at their neighboring PoIs. Numerical experiments show the efficacy of the proposed algorithms in comparison to other available algorithms in terms of overall error, coverage, and computational complexity. [ABSTRACT FROM AUTHOR]

In received signal strength target localization problems, the selection of sensor positions involved in estimation is a crucial factor in determining the network’s overall quality of estimation. In this paper, we consider a region of interest with: 1) several points of interest (PoIs) each assigned a localization error requirement and 2) candidate sensor positions at which sensors can be deployed/activated. Then, under sensor budget constraints, how can we select a limited number of sensors so that the overall localization error at the PoIs is best met in a squared error sense? Instead of directly using errors, we use corresponding sensor density information which results in the simplification of the selection problem. Using density information, we propose two novel sequential selection algorithms. In the first algorithm, selection is formulated as a sequential convex quadratic optimization problem in which the cost is a function of the difference between required and achieved sensor densities at the PoIs. Selection in the second algorithm uses density weights assigned to each candidate position and is performed in a greedy fashion. Performance evaluation of the proposed methods with respect to other algorithms shows their effectiveness. [ABSTRACT FROM AUTHOR]

In RSSI-based target localization, estimation error depends on several factors (e.g., location of sensors, target energy). Furthermore, when quantization is involved, localization accuracy largely depends on the number of allocated bits and quantization thresholds used by each sensor. In this paper, we consider the problem of meeting estimation error requirements at different points of interest within the deployment area as best as possible under a bit rate budget constraint. Due to the complexity of the problem, we first address the bit allocation problem by proposing three different sequential allocation algorithms. Simulation results indicate that the error performance of proposed algorithms is within 2% - 20% of that of the optimal solution. Secondly, we propose the ESAQ adaptive scheme that incorporates target parameters and error profile of each sensor in quantization threshold selection. Simulation results show that the ESAQ outperforms both the EDQ and EBHQ thresholding methods found in literature. [ABSTRACT FROM AUTHOR]

In distributed sensor networks (DSNs), localization errors are highly dependent on the relative location of sensors with respect to the target of interest. In this paper, we study the problem of relocating sensors from their initial deployment positions to new positions that would result in meeting estimation requirements at multiple points in a region of interest as best as possible. More specifically, we develop a distributed virtual forces (VF)-based sensor relocation algorithm in which each sensor locally calculates its next location. In the proposed algorithm, VF forces are constructed in such a way that enables fast sensor relocation with the goal of minimizing the difference between achieved and required estimation requirements. The proposed algorithm is scalable and requires minimal information exchange between a sensor and its neighboring sensors. Simulation results are used to verify the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Gain and offset represent two important measures to determine the accuracy of a comparator. Thus, analysis on these parameters is very important as they offer designers better understanding of the circuit and allow exploring trade-offs during design. In this paper, two methods were presented to derive a set of design equations that describe the gain, sensitivity, offset, and systematic mismatches observed in typical comparator circuits. A three-stage, fast complementary metal-oxide semiconductor (CMOS) comparator structure is analysed and simulated in order to validate the proposed methods. A 0.13 μm CMOS technology is used for simulations with 1.5 V supply voltage. Bisection theorem was used for gain and sensitivity analysis. Simulation results show that high gain improvement can be possible by using the design equations. The input offset voltage, due to mismatch in the width of the metal oxide semiconductor field-effect transistors (MOSFET) (W) and mismatches in the threshold voltages of the N and P type MOSFETs(VTHN, VTHP), is analysed using a proposed balanced method. The same comparator structure is used for the input offset voltage analysis. Simulations show that an offset improvement can be achieved following the design equations found through the proposed method. [ABSTRACT FROM PUBLISHER]

Background: Sepsis continues to take main stage in healthcare. Therefore, it remains crucial to elucidate contributors to sepsis mortality. The aim of this study is to determine the impact of race, insurance type, and code status on sepsis mortality in a community health system., Methods: We conducted a retrospective cohort study of inpatient adults of any sex, race, and insurance type with a diagnosis of sepsis, severe sepsis, septic shock, or pneumonia., Results: We included 913 patients, with an average age of 69 years for expired patients and 62 years for non-expiring patients (P < 0.0001). After controlling for other variables, patients who presented as comfort care arrest were 4.3 (95% confidence interval (CI): 1.8 to 9.9, P = 0.0007) times more likely to have died than full code patients. Those who were comfort care only were 10.6 (95% CI: 0.8 to 140.6, P = 0.0741) times more likely to have died than the full code, although this was not statistically significant., Conclusions: The results suggest that patients who are comfort care arrest have an increased risk of sepsis mortality. The results show no impact of insurance type or race on sepsis mortality, which is in contrast to some existing literature. The study suggests that institutions may need to investigate internal variables related to sepsis mortality., Competing Interests: The authors declare that they have no conflict of interest., (Copyright 2022, Jabri et al.)